Introduction to Bioinformatics Monday, November 15, 2010 Jonathan Pevsner [email protected]...

Introduction to Bioinformatics

Monday, November 15, 2010Jonathan Pevsner

[email protected]

M.E:800.707

• People with very diverse backgrounds in biology

• Some people with backgrounds in computer

science and biostatistics

• Most people (will) have a favorite gene, protein, or disease

Who is taking this course?

• To provide an introduction to bioinformatics with a focus on the National Center for Biotechnology Information (NCBI), UCSC, and EBI

• To focus on the analysis of DNA, RNA and proteins

• To introduce you to the analysis of genomes

• To combine theory and practice to help you solve research problems

What are the goals of the course?

Textbook

The course textbook has no required textbook. I wrote Bioinformatics and Functional Genomics (Wiley-Blackwell, 2nd edition 2009). The lectures in this course correspond closely to chapters.

I will make pdfs of the chapters available to everyone.

You can also purchase a copy at the bookstore, at amazon.com (now $60), or at Wiley with a 20% discount through the book’s website www.bioinfbook.org.

Web sites

The course website is reached via moodle: http://pevsnerlab.kennedykrieger.org/moodle(or Google “moodle bioinformatics”)--This site contains the powerpoints for each lecture, including black & white versions for printing--The weekly quizzes are here--You can ask questions via the forum--Audio files of each lecture will be posted here

The textbook website is:http://www.bioinfbook.orgThis has powerpoints, URLs, etc. organized by

chapter. This is most useful to find “web documents” corresponding to each chapter.

Literature references

You are encouraged to read original source articles(posted on moodle). They will enhance your understanding of the material. Readings are optional but recommended.

Themes throughout the course: the beta globin gene/protein family

We will use beta globin as a model gene/protein throughout the course. Globins including hemoglobin and myoglobin carry oxygen. We will study globins in a variety of contexts including

--sequence alignment--gene expression--protein structure--phylogeny--homologs in various species

Computer labs

There are no computer labs, but the seven weekly quizzes function as a computer lab. To solve the questions, you will need to go to websites, use databases, and use software.

Grading

60% moodle quizzes (your top 6 out of 7 quizzes). Quizzes are taken at the moodle website, andare due one week after the relevant lecture.

Special extended due date for quizzes due immediately after Thanksgiving and the New Year.

40% final exam Monday, January 10 (in class).Closed book, cumulative, no computer,short answer / multiple choice. Past exams will be made available ahead of time.

Google “moodle bioinformatics” to get here;Click “Bioinformatics” to sign in;The enrollment key you need is…

The password to get the book chapter pdf is…

Outline for the course (all on Mondays)

1. Accessing information about DNA and proteins Nov. 15

2. Pairwise alignment Nov. 22

3. BLAST Nov. 29

4. Multiple sequence alignment Dec. 6

5. Molecular phylogeny and evolution Dec. 13

6. Microarrays Dec. 20

7. Genomes Jan. 3

Final exam Jan. 10

Outline for today

Definition of bioinformatics

Overview of the NCBI website

Accessing information: accession numbers and RefSeq

Entrez Gene (and UniGene, HomoloGene)

Protein Databases: UniProt, ExPASy

Three genome browsers: NCBI, UCSC, Ensembl

Access to biomedical literature

• Interface of biology and computers

• Analysis of proteins, genes and genomes using computer algorithms and computer databases

• Genomics is the analysis of genomes. The tools of bioinformatics are used to make sense of the billions of base pairs of DNA that are sequenced by genomics projects.

What is bioinformatics?

On bioinformatics

“Science is about building causal relations between natural phenomena (for instance, between a mutation in a gene and a disease). The development of instruments to increase our capacity to observe natural phenomena has, therefore, played a crucial role in the development of science - the microscope being the paradigmatic example in biology. With the human genome, the natural world takes an unprecedented turn: it is better described as a sequence of symbols. Besides high-throughput machines such as sequencers and DNA chip readers, the computer and the associated software becomes the instrument to observe it, and the discipline of bioinformatics flourishes.”

On bioinformatics

“However, as the separation between us (the observers) and the phenomena observed increases (from organism to cell to genome, for instance), instruments may capture phenomena only indirectly, through the footprints they leave. Instruments therefore need to be calibrated: the distance between the reality and the observation (through the instrument) needs to be accounted for. This issue of Genome Biology is about calibrating instruments to observe gene sequences; more specifically, computer programs to identify human genes in the sequence of the human genome.”

Martin Reese and Roderic Guigó, Genome Biology 2006 7(Suppl I):S1,introducing EGASP, the Encyclopedia of DNA Elements (ENCODE) Genome Annotation Assessment Project

Tool-users

Tool-makers

bioinformatics

public healthinformatics

medicalinformatics

infrastructure

databases algorithms

Three perspectives on bioinformatics

The cell

The organism

The tree of life

Page 4

DNA RNA phenotypeprotein

Page 5

Time ofdevelopment

Body region, physiology, pharmacology, pathology

Page 5

After Pace NR (1997) Science 276:734

Page 6

DNA RNA phenotypeprotein

Growth of GenBank

Year

Bas

e p

airs

of

DN

A (

mil

lio

ns)

Seq

uen

ces

(mil

lio

ns)

1982 1986 1990 1994 1998 2002 Fig. 2.1Page 17

Growth of GenBank + Whole Genome Shotgun(1982-November 2008): we reached 0.2 terabases

Nu

mb

er

of s

eq

uen

ces

in G

en

Ban

k (m

illio

ns)

Ba

se p

air

s o

f DN

A in

Gen

Ba

nk (

bill

ions

) B

ase

pa

irs

in G

en

Ban

k +

WG

S (

billi

ons

)

0

20

40

60

80

100

120

140

160

180

200

1982 1992 2002 2008

Fig. 2.1Page 15

Arrival of next-generation sequencing: In two years we have gone from 0.2 terabases to

71 terabases (71,000 gigabases) (November 2010)

Fig. 2.1Page 15

DNA RNA protein

Central dogma of molecular biology

genome transcriptome proteome

Central dogma of bioinformatics and genomics

DNA RNA

cDNAESTsUniGene

phenotype

genomicDNAdatabases

protein sequence databases

protein

Fig. 2.2Page 18

GenBankEMBL DDBJ

There are three major public DNA databases

The underlying raw DNA sequences are identical

Page 14

GenBankEMBL DDBJ

Housedat EBI

EuropeanBioinformatics

Institute

There are three major public DNA databases

Housed at NCBINational

Center forBiotechnology

Information

Housed in Japan

Page 14

Taxonomy at NCBI:>200,000 species are represented in GenBank

Page 16http://www.ncbi.nlm.nih.gov/Taxonomy/txstat.cgi10/10

The most sequenced organisms in GenBank

Homo sapiens 14.9 billion basesMus musculus 8.9bRattus norvegicus 6.5bBos taurus 5.4bZea mays 5.0bSus scrofa 4.8bDanio rerio 3.1bStrongylocentrotus purpurata 1.4bOryza sativa (japonica) 1.2bNicotiana tabacum 1.2b

Updated Oct. 2010GenBank release 180.0Excluding WGS, organelles, metagenomics

Table 2-2Page 17

Outline for today








National Center for BiotechnologyInformation (NCBI)

www.ncbi.nlm.nih.gov

Page 23

NCBI homepage

Fig. 2.4Page 24

• National Library of Medicine's search service• 20 million citations in MEDLINE (as of 2010)• links to participating online journals• PubMed tutorial on the site or visit NLM:

http://www.nlm.nih.gov/bsd/disted/pubmed.html

Page 23

NCBI key features: PubMed

Entrez integrates…

• the scientific literature; • DNA and protein sequence databases; • 3D protein structure data; • population study data sets; • assemblies of complete genomes

Page 24

NCBI key features: Entrez search and retrieval system

BLAST is…

• Basic Local Alignment Search Tool• NCBI's sequence similarity search tool• supports analysis of DNA and protein databases• 100,000 searches per day

Page 25

NCBI key features: BLAST

OMIM is…

•Online Mendelian Inheritance in Man•catalog of human genes and genetic disorders•created by Dr. Victor McKusick; led by Dr. Ada Hamosh

at JHMI

Page 25

NCBI key features: OMIM

TaxBrowser is…

• browser for the major divisions of living organisms (archaea, bacteria, eukaryota, viruses)• taxonomy information such as genetic codes• molecular data on extinct organisms• practically useful to find a protein or gene from a species

Page 26

NCBI key features: TaxBrowser

Structure site includes…

• Molecular Modelling Database (MMDB)

• biopolymer structures obtained from

the Protein Data Bank (PDB)• Cn3D (a 3D-structure viewer)• vector alignment search tool (VAST)

Page 25

NCBI key features: Structure

Outline for today








Accession numbers are labels for sequences

NCBI includes databases (such as GenBank) that contain information on DNA, RNA, or protein sequences. You may want to acquire information beginning with a query such as the name of a protein of interest, or theraw nucleotides comprising a DNA sequence of interest. DNA sequences and other molecular data are tagged with accession numbers that are used to identify a sequenceor other record relevant to molecular data.

Page 26

What is an accession number?

An accession number is label that used to identify a sequence. It is a string of letters and/or numbers that corresponds to a molecular sequence.

Examples (all for retinol-binding protein, RBP4):

X02775 GenBank genomic DNA sequenceNT_030059 Genomic contigRs7079946 dbSNP (single nucleotide polymorphism)

N91759.1 An expressed sequence tag (1 of 170)NM_006744 RefSeq DNA sequence (from a transcript)

NP_007635 RefSeq proteinAAC02945 GenBank proteinQ28369 SwissProt protein1KT7 Protein Data Bank structure record

protein

DNA

RNA

Page 27

NCBI’s important RefSeq project: best representative sequences

RefSeq (accessible via the main page of NCBI)provides an expertly curated accession number thatcorresponds to the most stable, agreed-upon “reference”version of a sequence.

RefSeq identifiers include the following formats:

Complete genome NC_######Complete chromosome NC_######Genomic contig NT_######mRNA (DNA format) NM_###### e.g. NM_006744Protein NP_###### e.g. NP_006735

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Accession Molecule Method NoteAC_123456 Genomic Mixed Alternate complete genomicAP_123456 Protein Mixed Protein products; alternateNC_123456 Genomic Mixed Complete genomic moleculesNG_123456 Genomic Mixed Incomplete genomic regionsNM_123456 mRNA Mixed Transcript products; mRNA NM_123456789 mRNA Mixed Transcript products; 9-digit NP_123456 Protein Mixed Protein products; NP_123456789 Protein Curation Protein products; 9-digit NR_123456 RNA Mixed Non-coding transcripts NT_123456 Genomic Automated Genomic assembliesNW_123456 Genomic Automated Genomic assemblies NZ_ABCD12345678 Genomic Automated Whole genome shotgun dataXM_123456 mRNA Automated Transcript productsXP_123456 Protein Automated Protein productsXR_123456 RNA Automated Transcript productsYP_123456 Protein Auto. & Curated Protein productsZP_12345678 Protein Automated Protein products

NCBI’s RefSeq project: many accession number formats for genomic, mRNA, protein sequences

Outline for today








Access to sequences: Entrez Gene at NCBI

Entrez Gene is a great starting point: it collectskey information on each gene/protein from major databases. It covers all major organisms.

RefSeq provides a curated, optimal accession number for each DNA (NM_000518 for beta globin DNA corresponding to mRNA) or protein (NP_000509)

Page 29

From the NCBI homepage, type “beta globin”and hit “Search”

Fig. 2.5Page 28

Fig. 2.5Page 28

Follow the link to “Gene”

Entrez Gene is in the headerNote the “Official Symbol” HBB for beta globinNote the “limits” option

Using “limits” you can restrict your search to human (or any other organism)

By applying limits, there are now far fewer entries

Entrez Gene (top of page)

Note that links tomany other HBB database entries are available

Entrez Gene (middle of page): genomic region, bibliography

Entrez Gene (middle of page, continued): phenotypes, function

Entrez Gene (bottom of page): RefSeq accession numbers

Entrez Gene (bottom of page): non-RefSeq accessions(it’s unclear what these are, highlighting usefulness of RefSeq)

Fig. 2.8Page 31

Entrez Protein:accession, organism,literature…

Fig. 2.8Page 31

Entrez Protein:…features of a protein, and its sequence in the one-letter amino acid code

You should learn the one-letter amino acid code!

Name 3-Letter 1-LetterAlanine Ala AArginine Arg R

Asparagine Asn NAspartic acid Asp D

Cysteine Cys CGlutamic Acid Glu E

Glutamine Gln QGlycine Gly G

Histidine His HIsoleucine Ile I

Name 3-Letter 1-LetterLeucine Leu LLysine Lys K

Methionine Met MPhenylalanine Phe F

Proline Pro PSerine Ser S

Threonine Thr TTryptophan Trp W

Tyrosine Tyr YValine Val V

Entrez Protein:You can change the display (as shown)…

FASTA format:versatile, compact with one header line

followed by a string of nucleotides or amino acids in the single letter code

Fig. 2.9Page 32

Outline for today








Comparison of Entrez Gene to other resources

Entrez Gene, Entrez Nucleotide, Entrez Protein:closely inter-related

Entrez Gene versus UniGene: UniGene is a database with information on where in a body, when in development, and how abundantly a transcript is expressed

Entrez Gene versus HomoloGene:HomoloGene conveniently gathers

information on sets of related proteins

Page 32

DNA RNA

complementary DNA(cDNA)

protein

UniGeneFig. 2.3Page 22

HomoloGene: an NCBI resource organized by organism to describe where genes are expressed

(i.e. from which library) and how abundantly

HomologoGene: an excellent NCBI resource that conveniently groups homologous eukaryotic genes

(find links from Entrez search engine or Entrez gene)

Outline for today








ExPASy to access protein and DNA sequences

ExPASy sequence retrieval system(ExPASy = Expert Protein Analysis System)

Visit http://www.expasy.ch/

Page 33

UniProt: a centralized protein database (uniprot.org)

This is separate from NCBI, and interlinked.

Page 33

Fig. 2.10Page 34

ExPASy: vast proteomics resources (www.expasy.ch)

Outline for today








Genome Browsers:increasingly important resources

Genomic DNA is organized in chromosomes. Genome browsers display ideograms (pictures) of chromosomes, with user-selected “annotation tracks” that display many kinds of information.

The two most essential human genome browsers are at Ensembl and UCSC. We will focus on UCSC (but the two are equally important). The browser at NCBI is not commonly used.

clickhuman

Ensembl genome browser (www.ensembl.org)

enterbeta globin

Ensembl output for beta globin includes views of chromosome 11 (top), the region (middle), and a detailed view (bottom).

There are various horizontal annotation tracks.

The UCSC Genome Browser:an increasingly important resource

• This browser’s focus is on humans and other eukaryotes

• you can select which tracks to display (and how much information for each track)

• tracks are based on data generated by the UCSC team and by the broad research community

• you can create “custom tracks” of your own data! Just format a spreadsheet properly and upload it

• The Table Browser is equally important as the more visual Genome Browser, and you can move between the two

[1] Visit http://genome.ucsc.edu/, click Genome Browser

[2] Choose organisms, enter query (beta globin), hit submit

Page 36

[3] Choose the RefSeq beta globin gene

[4] On the UCSC Genome Browser:--choose which tracks to display--add custom tracks--the Table Browser is complementary

Example of how to access sequence data:HIV-1 pol

There are many possible approaches. Begin at the mainpage of NCBI, and type an Entrez query: hiv-1 pol

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11/10

Searching for HIV-1 pol: 150,000 nucleotide, protein hits

Example of how to access sequence data:HIV-1 pol

For the Entrez query: hiv-1 polthere are about 150,000 nucleotide or protein records(and >350,000 records for a search for “hiv-1”),but these can easily be reduced in two easy steps:

--specify the organism, e.g. hiv-1[organism]--limit the output to RefSeq!

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Searching for HIV-1 pol:using the command hiv-1[organism] limits the

output to just one entry

Try Taxonomy Browser to easily limit your query to your favorite organism(s). Example: NCBI home Taxonomy Taxonomy browser human protein to find a human protein

Entrez Nucleotide features over 360,000 nucleotide entries for HIV-1 (but only one RefSeq for that virus)

Example of how to access sequence data: histone

query for “histone” # results

protein records 104,000RefSeq entries 39,000

RefSeq (limit to human) 1171NOT deacetylase 911

At this point, select a reasonable candidate (e.g.histone 2, H4) and follow its link to Entrez Gene.There, you can confirm you have the right protein.

11-10

Entrez Gene result for a histone

Outline for today








PubMed at NCBIto find literatureinformation

PubMed is the NCBI gateway to MEDLINE.

MEDLINE contains bibliographic citations and author abstracts from over 4,600 journals published in the United States and in 70 foreign countries.

It has >20 million records dating back to 1950s.

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MeSH is the acronym for "Medical Subject Headings."

MeSH is the list of the vocabulary terms used for subject analysis of biomedical literature at NLM. MeSH vocabulary is used for indexing journal articles for MEDLINE.

The MeSH controlled vocabulary imposes uniformity and consistency to the indexing of biomedical literature.

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PubMed result for HBB

Use the pull-down menu to access related resources such as Medical Subject Headings (MeSH)

A “how to” pull-down menu links to tutorials

Use “Advanced search” to limit by author, year, language, etc.

PubMed search strategies

Try the tutorial

Use boolean queries (capitalize AND, OR, NOT)lipocalin AND disease

Try using limits (see Advanced search)

There are links to find Entrez entries and external resources

Obtain articles on-line via Welch Medical Library(and download pdf files): http://www.welch.jhu.edu/

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lipocalin AND disease(504 results)

lipocalin OR disease(2,500,000 results)

lipocalin NOT disease(2,370 results)

1 AND 2

1 OR 2

1 NOT 2

1

1

1

2

2

2

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WelchWeb is available at http://www.welch.jhu.edu

Welch Medical Library liasons to the basic sciences

WelchWeb is available at http://www.welch.jhu.edu

Reminder: Please enroll! Google “moodle bioinformatics” to get here; click “Bioinformatics” to sign in;The enrollment key is…

Introduction to Bioinformatics Monday, November 15, 2010 Jonathan Pevsner [email protected]...

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